Active medical device, including an implantable defibrillator, for detection of QRS complexes in a very noisy signal

ABSTRACT

An active implantable medical device (e.g., implantable pacemaker or defibrillator), for detection of QRS complexes in noisy signals. Functional units ( 12 - 16 ) collect, amplify, prefilter and convert from analog-to-digital an endocardial signal, and digital functional units ( 18 ) provide signal processing and analysis of the digitized signal, for delivery of an indicator corresponding to a signal peak detection representative of the presence of a QRS complex in the endocardial signal. A double threshold comparator ( 30 ) is employed, receiving as input ( 28 ) the digitized signal and outputting ( 40 ) the indicator of peak detection when, cumulatively: the amplitude (A) of the input signal exceeds a peak amplitude threshold (SA), and the peak amplitude threshold is exceeded for a period (W) greater than a peak width threshold (SW). The peak amplitude threshold (SA) is a variable adaptive threshold, according to a noise level calculated from the energy (RMS) of the input signal.

RELATED APPLICATIONS

The present application claims the priority date benefit of Frenchpatent application Ser. No. 11/53301 entitled “Active medical device,including an implantable defibrillator, for detection of QRS complexesin a very noisy signal” and filed Apr. 15, 2011, which is herebyincorporated by reference in its entirety.

FIELD

The present invention is directed to “active implantable medicaldevices” as defined by the 20 Jun. 1990 Directive 90/385/EEC of theCouncil of European Communities, more particularly to devices thatcontinuously monitor a patient's heart rhythm and delivers to the heart,if necessary, an electrical pulse for cardiac stimulation,resynchronization and/or a defibrillation, in response to a detectedcardiac arrhythmia.

BACKGROUND

Cardiac rhythm analysis is commonly performed from electrogram signals(EGM) collected by electrodes located on endocardial leads implanted inthe myocardium to measure the atrial and/or ventricular depolarizationpotential. These EGM signals are analyzed by the device, which deliversto the patient if necessary an appropriate therapy in the form of lowenergy stimulation pulses (for bradycardia pacing or resynchronizationof the ventricles) or high energy defibrillation shocks.

The cardiac rhythm analysis, and therefore the decision whether or notto deliver a therapy, however, can be affected by artifacts collected bythe endocardial lead. These artifacts can have various origins. A firstseries of artifacts corresponds to situations where the device not onlydetects the cardiac event itself, e.g., a wave of depolarization of thecavity in question, but also a disturbance associated with this eventand wrongly considered as another depolarization event that occurredafter the first, for example, a late depolarization wave, crosstalkdetected between different heart cavities, and far-field signaldetection.

A second series of artifacts, which are the subject of the presentinvention, are the artifacts from extrinsic noise and not related to adepolarization of the myocardium. This noise can have many origins,including, for example, the myopotentials associated with musclecontractions, electromagnetic interference (EMI) from electronicsurveillance equipment, electrical devices located nearby,electrosurgical instruments, communication systems, and the like.

In addition, the digital signal processing (“DSP”) units typically usedin active implantable medical device generate a certain noise level,which is added to the signal depolarization. In particular, the digitalfiltering can initially increase the amplitude of the signaloscillations before the amplitude slowly decreases as the systemstabilizes over time, with the consequence of disrupting the analysiscarried out downstream of this distorted signal.

In general, a noise that is present with varying regularity, whetherextrinsic or due to the specific digital processing, can be interpretedby the device as a depolarization of the myocardium, with the risk ofgenerating inappropriate therapy, such as wrongly inhibiting thebradycardia pacing or the resynchronization pacing, or conversely, byfalsely delivering inappropriate shocks.

Various techniques have been proposed to reduce the impact of extrinsicnoise, including the upstream application to the signal processingcircuits for analog or digital filtering, the introduction of refractoryperiods, the automatic adjustment of the sensitivity of the detectionamplifiers, or the automatic gain control of these amplifiers.

EP 0958843 A1 describes one technique of “autosensing”, wherein analgorithm continuously adapts the detection threshold depending on thelevel of noise and the amplitude of the EGM signals associated withdetected cardiac events. However, the use of these autosensing methodsis always at the expense of a good detection. In particular, to detectventricular fibrillation (VF), the signal level of which is consideredrelatively low, it is necessary to have a maximum sensitivity, in orderto prevent failing to detect events that should have been detected. Butthe signal amplitude of ventricular fibrillation (specifically, QRScomplexes indicative of ventricular depolarizations) may be of avariable level, between the noise signal level and the signal levelcorresponding to a sinus complex (a spontaneous depolorization).

Consequently, setting a threshold low enough to detect ventricularfibrillation runs the inevitable risk of also detecting a possiblenoise. If in addition there is a regular noise, for a patient withnormal sinus heart rhythm, this noise can be confused withdepolarizations. This may distort the evaluation of the average cardiacrate as determined by the device, with an (incorrectly) estimated rateof a level much higher than reality, and a corresponding risk ofapplying undesirable antitachycardia therapy (a false positivesituation, called “oversensing”).

Conversely, if the device is programmed to a too low sensitivity value,that is to say, with a too high detection threshold, the actual episodesof ventricular fibrillation may not be detected (a false negativesituation, called “undersensing”) with potentially serious consequencesfor the patient.

With the detection of extrinsic noise being usually inevitable, theproblem addressed by the present invention is to distinguish thesenoises from the actual heart depolarizations, in order to avoidtriggering inappropriate therapies and, conversely, inhibiting deliveryof therapies that if delivered would have been appropriate.

The identification of these noises and their mitigation by means offilters is a complex task, the main difficulty being the extremevariability of these spurious signal components, which impliesrelatively complex processing to be effective.

Complex digital processing techniques have been proposed for thispurpose to ensure the detection of a QRS complex in the endocardialsignal, including, for example, non-linear filtering, wavelet transform,artificial network, genetic algorithm and linear prediction techniques.These various, complex, algorithms require a large number of arithmeticoperations and require significant computing resources, with a furthersignificant increase in energy consumption by the device, consequentlyhaving an impact on the useful life of the implanted device.

Another technique, described, for example, in EP 0775502 and itscounterpart U.S. Pat. No. 5,836,980 (both assigned to Sorin CRM S.A.S,previously known as ELA Medical), is to analyze the signalcharacteristics by deriving it by differentiating means to assess theinstantaneous variations of the signal by comparing them topredetermined thresholds. The required circuits are relatively simplebut, however, they enable a relatively limited discrimination in thecase of highly noisy signals.

Yet another technique was proposed by EP 1857142 A1 and its counterpartU.S. Pat. Publication No. 2007/0282379 (both assigned to Sorin CRMS.A.S., previously known as ELA Medical), which is to conduct a doubledetection by analysis of the depolarization of the EGM electricalsignal, and of the contraction of the myocardium by measuring theendocardial acceleration (EA), the latter obtained via an accelerometerin direct contact with the heart muscle. In the presence of noises, thedevice operates an alarm verification to confirm that the detectedsignal has actually been followed by a mechanical activity of the heartand thus constitutes a signal of depolarization (QRS complex) and not anartifact. In this regard, the depolarization is an electrical phenomenonsensitive to noise and is indeed usually followed by cardiaccontraction, a mechanical phenomenon that is not affected by the samenoise.

But this presupposes to have a lead equipped with an endocardialacceleration sensor, and if the patient already has an implanted device,implies during a change in the generator to change not only thegenerator but also the lead, which is a much more difficult surgery.

EP 0429025 A2 describes a technique to make a double discrimination,both on the amplitude and on the width of the peaks of detected signal:a first amplitude discrimination is used to extract only signalsexceeding a given level, while the analysis of the width of the signalbeing above this threshold amplitude discriminates a possible parasiticcomponent that would not have been eliminated in the filtering upstreamof this processing. U.S. Pat. No. 4,000,461 describes a comparabletechnique of discrimination by amplitude/duration cross-analysis of thepeaks of detected signal. The thresholds for comparison (amplitude andwidth) are adjustable, and adjusted to a value chosen by thepractitioner during the programming of the device. This presupposes,however, that the conditions at the time of adjustment remain fairlyconstant over time, for an effective discrimination. But in practicethis is rarely the case, making this technique unreliable for detectingthe presence (or not) of a QRS complex in the received endocardialsignal, especially to detect ventricular fibrillation for which, asexplained above, the useful signal can be at a variable level,intermediate between the noise and the signals of the sinus complexes.Because of the fixed parameters, the risks of oversensing orundersensing are then particularly high, with the potential seriousconsequences that have been outlined above.

OBJECTS AND SUMMARY

It is, therefore, an object of the present invention is to provide anendocardial signal processing to effectively discriminate spurious noisecomponents to reliably detect the presence (or not) of a QRS complex inthe collected endocardial signal.

It is another object of the present invention to provide suchendocardial signal processing with reduced need for computing power fordigital processing, resulting in a preservation of the battery power anduseful life of the implantable device.

It is yet another object of the present invention to propose such anendocardial signal processing that can be used regardless of the type oflead used, this feature being particularly advantageous when replacingonly the generator of the implantable device without replacing thelead(s) already present.

The present invention is broadly directed to providing a doublediscrimination threshold (amplitude and duration of the peak), butwherein the amplitude threshold for discriminating between signal andnoise is a variable, adaptive threshold, updated based on the averagenoise level determined in the absence of detected depolarizationsignals. Preferably the discrimination amplitude threshold is regularlyupdated according to the level exceeding the threshold.

One aspect of the present invention is for a device of the generic typedisclosed in EP 0429025 A2 above, namely an active implantable medicaldevice having circuits for collecting, amplifying, prefiltering andanalog-to-digital conversion of a collected endocardial signal, anddigital signal processing circuits for analyzing the digitizedendocardial signal, for delivering an indicator corresponding to adetection of a signal peak representative of a QRS complex present inthe endocardial signal. The digital processing and analysis circuitshave a dual threshold for the comparator, receive as input the digitizedsignal, and output the indicator for a peak detection when,cumulatively: the amplitude of the input signal exceeds a peak amplitudethreshold, and the peak amplitude threshold, and the peak widththreshold.

In one embodiment of the present invention, the peak amplitude thresholdis a variable adaptive threshold, and the digital processing andanalysis circuit further comprises means for determining a peakamplitude threshold, by combining a predetermined base threshold valueand a variable noise level of the input signal, and means fordetermining a variable noise level value from the noise present in thedigitized input signal, outside of the periods of detection of signalpeak.

In a preferred embodiment, the means for determining the value of thevariable noise level comprises means for calculating the energy of theinput signal over a predetermined calculation period during which theamplitude of the input signal does not exceed said peak amplitudethreshold. In a more preferred embodiment, the device may furtherinclude means for inhibiting and resetting the means for determining thevariable noise level value, in response to a crossing of said peakamplitude threshold before expiry of the predetermined calculationperiod.

The peak width threshold is preferably a fixed, predetermined threshold.

Advantageously, the digital processing and analysis circuits alsoinclude a low pass filter for filtering the input signal, as well as ahigh-pass filter and a rectifier, to filter and rectify the signalapplied to the low pass filter.

DRAWINGS

Further features, characteristics and advantages of the presentinvention will become apparent to a person of ordinary skill in the artfrom the following detailed description of preferred embodiments of thepresent invention, made with reference to the drawings annexed, in whichlike reference characters refer to like elements, and in which:

-   -   FIG. 1 is a block schematic diagram for detecting the QRS        complexes in accordance with a preferred embodiment of the        present invention;    -   FIG. 2 illustrates graphically a double detection, in amplitude        and in width, of the input signal of FIG. 1;    -   FIG. 3 is a machine sequence state diagram illustrating the        different states of the analysis and update algorithm of the        adaptive threshold according to the invention; and    -   FIGS. 4 a to 4 d show various possible wave depolarization        configurations, to illustrate detection of the QRS complex and        for the update of the amplitude threshold in accordance with the        present invention.

DETAILED DESCRIPTION

An example of a preferred embodiment of a device of the presentinvention will now be described with reference to the drawings FIGS.1-3.

As regards its software aspects, the present invention can beimplemented by an appropriate programming of the control softwareinstructions of a known device, for example, a cardiac pacemaker or adefibrillator/cardioverter, including circuits for collecting a signalprovided by endocardial leads and/or one or more implanted sensors. Thepresent invention may particularly be applied to implantable devicessuch as those of the Reply and Paradym device families produced andmarketed by Sorin CRM, Clamart France, formerly known as ELA Medical,Montrouge, France.

These devices include signal conditioning circuits and programmablemicroprocessor circuitry including central processing units, registersand memory able to receive, format, and process electrical signalscollected (detected) by implanted electrodes and to deliver electricalpulses to these electrodes for stimulation, cardioversion and/ordefibrillation. It is possible to transmit by known telemetry technologysoftware instructions that will be stored in a memory of the implantabledevice and executed to implement the functions of the present inventionthat will be described herein. The adaptation of these known devices toimplement the functions and features of the present invention isbelieved to be within the abilities of a person of ordinary skill in theart, and therefore will not be described in detail.

Also, it should be understood that the present invention is preferablyimplemented by use of software instructions, with appropriate algorithmsexecuted by a microcontroller or alternatively a digital signalprocessor. For the sake of clarity, the various processing features ofpresent invention to be applied are decomposed and represented by anumber of different functional blocks in the form of interconnected“circuits”, but this representation is only illustrative, however, andthese “circuits” including common elements and corresponding in practiceto a plurality of functions generally may be performed by the samesoftware.

FIG. 1 illustrates in the form of functional blocks, one embodiment ofthe different elements for the detection of the QRS complex of aventricular depolarization signal, especially in the case of ventricularfibrillation, from an endocardial signal collected by the electrodelocated at the termination of a lead connected to the generatorincorporating this detection circuit.

This system includes an analog part followed by a digital part.

First, the endocardial EGM signal is applied to the input 10 ofamplifier 12 and of an analog bandpass filter 14, such as a Butterworthfilter, defined by relatively wide limits (typically between 4 and 130Hz). The amplified and filtered signal is then input to ananalog-to-digital converter 16, for a conversion, for example, to 10bits, at a sampling frequency of 512 Hz.

The digitized raw signal is processed by the digital block 18, in orderto detect the presence of a QRS complex. The digitized signal fromconverter 16 is applied to a high-pass filter 20 so as to eliminate anyDC component that may be present (and thus avoid saturation ofdownstream processing circuits), and also to enhance certaincharacteristic components of the EGM signal. This high-pass filter 20 ispreferably, for example, a third order Butterworth filter with a cutofffrequency of 25 Hz. Such a filter provides a rapid stabilization of theoutput signal with few oscillations (for a level signal applied to theinput). It also has the advantage of consuming relatively little powerand not being very demanding in terms of computing resources. The filtermay involve converting the ten bit input digital values to an eight bitvalue, e.g., to limit the dynamic range of the signal.

The next stage is a rectifier 22, which transforms the digitized signalto all positive values and thereby simplifies the subsequent arithmeticoperations. While this feature introduces non-linearities, it simplifiesfurther processing (for example, needing only to evaluate positivethresholds when evaluating the amplitude of the signal), and providesgreater flexibility and simplification of decision rules of the presence(or not) of a QRS complex.

The rectifier 22 is followed by a low pass filter (24) for increasingthe resolution width of the rectified and filtered signal, e.g.,converting the eight bit digital values into twelve bit values, toincrease the accuracy of the rectifier and filter. This is because, asshall be discussed later, the analysis of this signal implies a widthanalysis of the signal peaks that were detected, to increase theefficiency of the discrimination compared to the noise. Low-pass filter24 is preferably, for example, a second order Butterworth filter with acutoff frequency of about 80 Hz, and preferably a digital filter withinfinite impulse response (IIR), which has a relatively low responsetime. A quick filter provides for the possibility to start the algorithmfor QRS detection faster.

The signal thus filtered at the output of filter 24 is then applied atthe input of a gain stage 26, the value of which is chosen so as not tosaturate the system downstream. The gain stage may involve convertingthe twelve bit digital values to eight bit values, e.g., to limit thedynamic range of the signal. The resulting signal is applied to theinput 28 of a comparator 30, which is preferably a dual thresholdcomparator of amplitude and of width.

Comparator 30 first analyzes the amplitude A of the signal compared tothe amplitude threshold SA and, when the amplitude threshold SA iscrossed, analyzes the width W of the amplitude peak compared to thewidth threshold SW. In other words, for the comparator to switch theindicator from a first state (e.g., a logical low value such as “0”) toa second state (e.g., a logical high value such as “1”) to indicate thepresence of a QRS complex detection, it is necessary that both theamplitude A of the signal exceeds the threshold SA, and that thisthreshold SA is exceeded for a period W (peak width) greater than thewidth threshold SW.

The width threshold SW is preferably a predetermined value W₀, fixed orset.

However, the amplitude threshold SA is a variable threshold, one that isadaptive depending on the average noise level during a given period. Theadaptive amplitude threshold SA is determined by a circuit 32 thatdetermines the noise level. Circuit 32 receives as input the samedigital signal as that applied to the input of comparator 30, but onlyduring the periods when it does not exceed the amplitude threshold SA.The noise level is, for example, determined from measure of the energy,more preferably the root mean square (RMS) based on a series of samplesduring a predetermined calculation period T_(RMS). For reasons ofeconomy of energy consumption, the calculation of RMS is preferablylimited to a relatively short duration, such as T_(RMS)=32 ms.

The RMS average value obtained is added by an adder 34 to apredetermined base threshold A₀ applied as input 36 of adder 34. Theresulting value SA=A₀+RMS is applied to the input of the comparator 30as a reference value of the amplitude threshold SA.

Circuit 32 for calculating the RMS is, as indicated by dashed line 42,coupled to the output 40 of the comparator 30 so as to calculate the RMSvalue only in certain signal conditions, as is described below.

In summary, the present invention proposes, after prior conditioning ofthe digitalized signal by appropriate filtering, to operate on the inputsignal, a selection based on energy between the noise peaks and theuseful signal peaks. In other words, the detection of a peak by means ofa dual threshold comparator (amplitude and width) offers the possibilityto decorrelate the useful signal and the noise and to determine, undercertain conditions (see, for example, the explanations given below withreference to FIG. 3), the triggering of the RMS average value associatedwith the signal. This value, calculated during a certain time durationcombined with a predetermined threshold value, and thus allows a regularupdating of the amplitude threshold.

Referring to FIG. 2, a form of filtered digitized signal as applied atthe input of the dual-stage comparator 30 is illustrated. This signal isin the form of a succession of discrete samples A_(i), A_(i+1), A_(i+2),. . . .

Comparator 30 detects first the samples having an amplitude greater thanthe amplitude threshold SA. If the width W of the signal peak (i.e., theportion of the signal that exceeds the threshold SA) exceeds a widththreshold SW (that is, if the number of consecutive samples above thethreshold SA exceeds a given number), then the signal peak is consideredto represent an actual QRS complex. In other words, if the twothresholds of amplitude and width are cumulatively exceeded, the deviceconsiders that there is actual presence of a ventricular depolarization.

As noted above, the width threshold SW is a fixed threshold W₀, which isconfigurable, while the amplitude threshold SA is a variable, adaptive,threshold which varies with the noise level of the analyzed signal, thisnoise being composed of all the random noise not representative offluctuations associated with the cardiac depolarization.

FIG. 3 illustrates in the form of a state machine diagram the sequenceof the different steps of the algorithm for i) the detection of QRS, ii)the calculation of noise level, and iii) the update of the amplitudethreshold.

Initially (block 100), the device is waiting for a peak detection, morespecifically, waiting for a sample having an amplitude that exceeds theamplitude threshold SA (A>SA).

If such a peak is detected, the machine state changes (block 110) towait until the detection of the end of the peak (namely, detection ofthe first of the subsequent samples having an amplitude A that fallsbelow the amplitude threshold level SA). The width W of the peak is thendetermined (this width corresponding to the number of consecutivesamples having amplitude A above the amplitude threshold SA). If thiswidth W is greater than the width threshold SW, then it is consideredthat the QRS complex was actually detected (block 120). If not, thealgorithm returns to block 100.

When the sample amplitude A falls below the threshold SA (A<SA), thealgorithm starts calculating the noise level (block 130). Thiscalculation is made over a given period T_(RMS) (e.g., T_(RMS)=32 ms),provided that the sample amplitudes A remain below the threshold SA,otherwise, the algorithm cancels the calculation of noise level andreturns to block 110. In the latter circumstance, if the sampleamplitude A is above the threshold SA, it is considered that a new peakhas been detected and will be analyzed, and the time the amplitude wasbelow the threshold SW was less than T_(RMS) and not long enough for thecalculation of noise.

If the period T_(RMS) has fully elapsed with the sample amplitude Aremaining below the threshold SA, then this threshold is updated (block140). The new threshold SA′ is calculated with the new updated value ofthe RMS noise (SA′=SA+RMS).

FIGS. 4 a to 4 d show four different configurations of the analyzedsignal applied to the input of the dual-threshold comparator, toillustrate the corresponding actions taken as appropriate.

FIG. 4 a illustrates a signal having an amplitude A that always remainsbelow the threshold SA: In this case, the output of the dual thresholdcomparator 30 remains ‘0’ (corresponding to an “absence of detectedQRS”), and the value of the threshold SA remains unchanged. Nocalculation of noise level is triggered.

FIG. 4 b illustrates a signal having an amplitude A that exceeds thethreshold SA, but over a period (width W) below the required widththreshold SW. In this case, the detected peak is likely a noise spuriouspeak, and no action is taken, as in the previous case.

FIG. 4 c illustrates the case wherein the signal amplitude A exceeds theamplitude threshold SA for a period W greater than the width thresholdSW. In this case, it is considered that there is QRS detection (hence anoutput ‘1 is’ delivered by comparator 30). Note that this detectionsignal is delivered with a delay relative to the start of the peak, adelay equal to the number of samples required to reach the widththreshold SW. But this delay is relatively small: when the SW thresholdis crossed, the signal is delivered by comparator 30.

Once the width threshold SW is reached, the algorithm then waits untilthe amplitude A falls below the threshold SA (e.g., the sampledesignated X in FIG. 4 c). The calculation of the noise level is thentriggered during the prescribed duration T_(RMS) (T_(RMS)=32 ms). Duringall the duration T_(RMS) of the calculation of noise level, theamplitude threshold SA is maintained at its previous value. At the endof the calculation, the amplitude threshold is automatically updated,from the value SA to the value SA′=A₀+RMS (A₀ being the base threshold,and RMS being the value of noise level which has just been calculated).

Finally, FIG. 4 d illustrates a configuration wherein two close peaksare successively detected, with the start time of the second peak beinglocated in a time interval ΔT of the beginning of the first peak. Inthis case:

-   -   If ΔT is below a predetermined period T_(MASK), the two        successive peaks are considered as a single peak, and only one        QRS detection signal is output (i.e., the two close peaks are        considered as a single QRS complex);    -   If, however, the second peak is detected with ΔT>T_(MASK), then        the two peaks are considered as two separate peaks, representing        two distinct QRS complexes;    -   Furthermore, if the beginning of the second peak is detected        before the end of the T_(RMS) calculation of the noise level,        then this noise calculation is canceled and the amplitude        threshold SA remains unchanged. The calculation of the noise        level will, however, be performed after the end second amplitude        peak.

The detection technique according to the present invention was tested onacquired data for twenty patients in the Sorin CRM database havingimplanted devices whose ECG waveforms contained significant noise andthus reflected the highest rate of false positive detections in theSorin CRM database. With conventional detection systems, the averagerate of detection of false positives (oversensing), that is, the ratioof the number of amplitude peaks wrongly detected as QRS, compared tothe total number of indicators of output peak detection delivered, wasabout 80%. With the present invention applied as described in theforegoing embodiment, the average rate of detection of false positiveswas reduced to about 18%, a decrease of more than four times the numberof false detections, other things being equal.

One skilled in the art will understand the present invention is notlimited by, and may be practice by other than the foregoing embodimentsdescribed, which are presented for purposes of illustration and not oflimitation.

The invention claimed is:
 1. An active implantable medical device,comprising means for collecting, amplifying, prefiltering and convertingfrom analog-to-digital an endocardial signal, means for digitallyprocessing and analyzing the digitized endocardial signal, and fordelivering an indicator of signal peak detection representative of apresence of a QRS complex in the endocardial signal, wherein thedigitized endocardiac signal has an amplitude, the means for digitalprocessing and analyzing comprises a double threshold comparator, havingas an input said digitized endocardial signal, a peak amplitudethreshold and a peak width threshold and having as an output saidindicator of peak detection in response to, cumulatively: the digitizedendocardiac signal amplitude exceeding said peak amplitude threshold;and said peak amplitude threshold is exceeded for a period greater thansaid peak width threshold; wherein said peak amplitude threshold is avariable adaptive threshold, and wherein the means for digitallyprocessing and analyzing further comprises: means for determining saidpeak amplitude threshold, by combining a predetermined base thresholdand a variable value of noise level of the input endocardial signal; andmeans for determining said variable value of noise level based upon anenergy (root mean square (RMS)) of the noise present in the input signaloutside of the periods of said digitized endocardial signal amplitudeexceeding said peak amplitude threshold.
 2. The device of claim 1,wherein the means for determining said variable value of noise levelfurther comprises means for calculating an energy of the endocardialinput signal during a predetermined computing period during which thedigitized endocardial signal amplitude does not exceed said peakamplitude threshold.
 3. The device of claim 2, further comprising meansfor inhibiting and resetting the means determining the variable value ofnoise level in response said digitized endocardial signal amplitudeexceeding said peak amplitude threshold before expiration of saidpredetermined computing period.
 4. The device of claim 1, wherein saidpeak width threshold is a fixed predetermined threshold.
 5. The deviceof claim 1, wherein the means for digital processing and analyzingfurther comprises: A low-pass filter, for filtering said inputendocardial signal.
 6. The device of claim 5, wherein the means fordigital processing and analyzing further comprises: A high-pass filterand a rectifier, for filtering and rectifying the signal applied to thelow-pass filter.